Highlighting the Probabilistic Behavior of Occupants’ Preferences in Energy Consumption by Integrating a Thermal Comfort Controller in a Tropical Climate

The thermal comfort of an individual is known as the mental satisfaction they possess in a medium. This depends on several ambient factors such as air temperature, mean radiant temperature, relative humidity, air velocity, and personal factors such as cloth and metabolic activity. In buildings, occupants interact with different systems and equipment such as air conditioning, ventilation, lighting, and other appliances to influence these factors or demonstrate adaptive tendencies with the systems to reach comfort. Within the last two decades, preference-based occupant-centered control systems have been incorporated into buildings, generally validated with comfort indexes. A frequently found challenge is the formulation of the method used to create a system that considers the stochastic characteristics of the occupant’s portrait. Here, a method that links the advantages of both probabilistic and schedule-based methods and satisfactorily integrates it with comfort indexes through a controller is proposed. It is intended to compare the controller’s effect on thermal comfort through comfort indexes and energy consumption when implementing different occupant models applied in Panama. Sensibility analysis, gray-box building modeling, and thermal indexes were used in the controller’s design. Results showed that the best controller is the probability-based model providing low power consumption and PMV levels.